""" FILE: app/core/chunking/chunking_strategies.py DESCRIPTION: Mathematische Splitting-Strategien. AUDIT v3.3.2: 100% Konformität zur 'by_heading' Spezifikation. - Implementiert Hybrid-Safety-Net (Sliding Window für Übergrößen). - Breadcrumb-Kontext im Window (H1 > H2). - Sliding Window mit H1-Kontext (Gold-Standard v3.1.0). """ from typing import List, Dict, Any, Optional from .chunking_models import RawBlock, Chunk from .chunking_utils import estimate_tokens from .chunking_parser import split_sentences def _create_context_win(doc_title: str, sec_title: Optional[str], text: str) -> str: """Baut den Breadcrumb-Kontext für das Embedding-Fenster.""" parts = [] if doc_title: parts.append(doc_title) if sec_title and sec_title != doc_title: parts.append(sec_title) prefix = " > ".join(parts) return f"{prefix}\n{text}".strip() if prefix else text def strategy_sliding_window(blocks: List[RawBlock], config: Dict[str, Any], note_id: str, context_prefix: str = "") -> List[Chunk]: """ Fasst Blöcke zusammen und schneidet bei 'target' Tokens. Ignoriert H2-Überschriften beim Splitting, um Kontext zu wahren. """ target = config.get("target", 400) max_tokens = config.get("max", 600) overlap_val = config.get("overlap", (50, 80)) overlap = sum(overlap_val) // 2 if isinstance(overlap_val, tuple) else overlap_val chunks: List[Chunk] = [] buf: List[RawBlock] = [] def _add(txt, sec, path): idx = len(chunks) # H1-Kontext Präfix für das Window-Feld win = f"{context_prefix}\n{txt}".strip() if context_prefix else txt chunks.append(Chunk( id=f"{note_id}#c{idx:02d}", note_id=note_id, index=idx, text=txt, window=win, token_count=estimate_tokens(txt), section_title=sec, section_path=path, neighbors_prev=None, neighbors_next=None )) def flush(): nonlocal buf if not buf: return text_body = "\n\n".join([b.text for b in buf]) sec_title = buf[-1].section_title; sec_path = buf[-1].section_path if estimate_tokens(text_body) <= max_tokens: _add(text_body, sec_title, sec_path) else: sents = split_sentences(text_body); cur_sents = []; cur_len = 0 for s in sents: slen = estimate_tokens(s) if cur_len + slen > target and cur_sents: _add(" ".join(cur_sents), sec_title, sec_path) ov_s = []; ov_l = 0 for os in reversed(cur_sents): if ov_l + estimate_tokens(os) < overlap: ov_s.insert(0, os); ov_l += estimate_tokens(os) else: break cur_sents = list(ov_s); cur_sents.append(s); cur_len = ov_l + slen else: cur_sents.append(s); cur_len += slen if cur_sents: _add(" ".join(cur_sents), sec_title, sec_path) buf = [] for b in blocks: # H2-Überschriften werden ignoriert, um den Zusammenhang zu wahren if b.kind == "heading": continue if estimate_tokens("\n\n".join([x.text for x in buf])) + estimate_tokens(b.text) >= target: flush() buf.append(b) flush() return chunks def strategy_by_heading(blocks: List[RawBlock], config: Dict[str, Any], note_id: str, doc_title: str = "") -> List[Chunk]: """ Splittet Text basierend auf Markdown-Überschriften mit Hybrid-Safety-Net. """ strict = config.get("strict_heading_split", False) target = config.get("target", 400) max_tokens = config.get("max", 600) split_level = config.get("split_level", 2) overlap = sum(config.get("overlap", (50, 80))) // 2 chunks: List[Chunk] = [] buf: List[str] = [] cur_tokens = 0 def _add_to_chunks(txt, title, path): idx = len(chunks) win = _create_context_win(doc_title, title, txt) chunks.append(Chunk( id=f"{note_id}#c{idx:02d}", note_id=note_id, index=idx, text=txt, window=win, token_count=estimate_tokens(txt), section_title=title, section_path=path, neighbors_prev=None, neighbors_next=None )) def _flush(title, path): nonlocal buf, cur_tokens if not buf: return full_text = "\n\n".join(buf) if estimate_tokens(full_text) <= max_tokens: _add_to_chunks(full_text, title, path) else: sents = split_sentences(full_text); cur_sents = []; sub_len = 0 for s in sents: slen = estimate_tokens(s) if sub_len + slen > target and cur_sents: _add_to_chunks(" ".join(cur_sents), title, path) ov_s = []; ov_l = 0 for os in reversed(cur_sents): if ov_l + estimate_tokens(os) < overlap: ov_s.insert(0, os); ov_l += estimate_tokens(os) else: break cur_sents = list(ov_s); cur_sents.append(s); sub_len = ov_l + slen else: cur_sents.append(s); sub_len += slen if cur_sents: _add_to_chunks(" ".join(cur_sents), title, path) buf = []; cur_tokens = 0 for b in blocks: if b.kind == "heading": if b.level < split_level: _flush(b.section_title, b.section_path) elif b.level == split_level: if strict or cur_tokens >= target: _flush(b.section_title, b.section_path) continue bt = estimate_tokens(b.text) if cur_tokens + bt > max_tokens and buf: _flush(b.section_title, b.section_path) buf.append(b.text); cur_tokens += bt if buf: last_b = blocks[-1] if blocks else None _flush(last_b.section_title if last_b else None, last_b.section_path if last_b else "/") return chunks